Network Performance Bottleneck Detection and Maximum Network Throughput Estimation for Datacenter Applications

Abstract

For applications deployed in third-party datacenter environments to attain cost-effective performance, it requires precise provisioning of hardware resources such as assigning appropriate network bandwidth to an application. However, it is not always clear how much resource should be assigned to an application. In this work, we propose NBD (Network performance Bottleneck Detector) to detect the network bandwidth requirement of a datacenter application. NBD is fully transparent and does not require modification of applications. It correctly reports the required bandwidth of an application even when the preset network bandwidth is far below the required bandwidth. NBD employs a novel technique called network flow distortion for the estimation of application network bandwidth requirement. The evaluation results indicate that NBD is effective and only incurs mild performance overhead.